Tag Archives: demographics
As retailers in 2017 continue to face headwinds, the competition is more challenging than ever. Customers are empowered by 24/7 access to the global marketplace. For many retailers, new store growth has slowed, so sales and margin growth are increasingly being driven more by incremental growth from existing stores. To continue to excel in this environment, every business should be mindful of three trends in retail big data:
- Sustainable growth – To grow sales in their existing stores, retailers must find innovative ways to reach customers and drive loyalty.
- Connected consumers – As consumers have become accustomed to growing transparency around the prices and quality of what they buy, retailers must find new ways to engage with and earn the loyalty of their customers.
- Explosion of big data – With the Internet of Things (IoT) maturing, retailers must leverage the vast amounts of useful data available within the network of devices and sensors that are connected online.
Retailers already have access to myriad data from sources like point of sale (POS), mobile devices, inventory management systems, and in-store sensors. As useful as this data is on its own, real insights happen when retailers can connect disparate data to see the conditions that bring success. And one powerful way to do this is by viewing data through the lens of location. Maps enable people to instantly spot and explore patterns and relationships in data.
Location is the common thread of data and enables decisions to be made about matters such as where to position existing merchandise and where to site new stores. Spatial analysis also allows retailers to more efficiently drive traffic through stores by effectively using the data typically only used in the online shopping environment. By tapping into insights derived from in-store sensors and customer mobile devices, retailers can make better decisions about where to allocate goods and employees in a strategic way that is targeted to consumer behavior. Forming a business strategy that leverages integrated location data helps retailers match the in-store customer experience with what consumers experience when shopping online. This is made possible by analyzing demographics, buying patterns, and customer movement in the context of space and time.
Spatial analysis is the key to understanding where, when, and why things happen. With this insight, retailers can engage existing and potential customers and spur in-store sales.
By Jessica Wyland
To identify customers, many product manufacturers are turning to location-based data. A recent Harvard Business Review article reported the use of “increasingly granular data, from detailed demographics and psychographics” including age, gender, address, income, and lifestyle.
“You’d be surprised how often a product manufacturer discovers that unexpected consumer groups are accounting for more purchases,” says James Hibbard, an expert in location intelligence and GIS manager for MarketSource.
MarketSource, a proven alternative to sales outsourcing, provides comprehensive solutions for the entire sales ecosystem. Hibbard uses data and maps to help MarketSource’s Fortune 500 clients determine who is actually buying at the retail level. One of the tools Hibbard relies on is ArcGIS Maps for Office.Continue reading
For many Americans, the rise in student loan debt means slowing economic recovery, delaying lifestage changes, and even postponing retirement.
Usually considered an issue that impacts only recent college graduates, new studies find that student loan debt is growing among pre-retirees and even those who have already retired. The 2013 Survey of Consumer Finances (SCF) notes that the rise in student loan debt is pervasive and affects nearly every age group. Families with education loans increased between 2010 and 2013, continuing the long-term trend of rising education debt. Forty-five percent of all American families have outstanding student loans, up from 33 percent in 2007. Between 2001 and 2013, education debt increased from 22.4 percent to 38.8 percent for young families—a household headed by someone younger than age 40.
How is this situation impacting the overall US economy?
Because of their student loans, many younger people are delaying home ownership, marriage, and having kids until their finances improve. Because most of this group aren’t establishing their own households now, growth of the broader economy remains sluggish. Many aren’t buying houses, or items such as furnishings, baby/children’s products, or home improvement/construction materials.
Esri’s World Population Estimate, a new probability surface that estimates the location and count of people throughout the world, is now available in ArcGIS Online.
Esri has been producing a global population estimate in ArcGIS Online for several years. This data is in the form of point features with population counts and characteristics assigned to each point; and it is used behind the scenes in apps such as Business Analyst Online, Community Analyst, and Esri Maps Apps. That may sound simple, but those points are big data; with nearly a billion locations represented. The Geographic Data Enrichment tools depend on those points as the basis for describing the characteristics of local populations in countries lacking a census or countries that do not make detailed census data available.
Based on this earlier point data work, Esri released the World Population Estimate (WPE) in December 2014. WPE takes the form of a raster surface, which is far easier to make available in ArcGIS Online and use in analysis models than the previous point data. Continue reading
While their behaviors confound retailers and marketers, we’re starting to gain a better understanding of what makes this cohort click.
Do you know any Millennials? You might even be a Millennial yourself.
Milliennials are contradictions, alternately described as lazy, entitled, idealistic, close to family, and racially diverse. Pew Research notes that Millennials are not bound to organized politics or religion, support a more activist government, are linked by social media, carry debt, and are optimistic about the future.
Demographers disagree about the exact time frame this huge group encompasses. Some say that Millennials were born between 1982 and sometime in the early 2000s. Pew Research says that Millennials range in age from 18 to 33 years. Continue reading
“Are we there yet?”
Vacationing parents usually answer this familiar question with a resounding “No!” The inquiry also resonates with economists who agree that median household income in the United States is “not there yet.”
Median household income is nowhere near the pre-Great Recession figures. According to Esri’s Updated Demographics data, median household income was $53,150 in 2007. During calendar year 2008 (the first year after the start of the recession), median household income rose to $54,700. In the intervening years, median household income fell from $54,700 in 2009 to $54,442 in 2010, and dropped in 98 percent of US counties. In 2013, Esri’s Updated Demographics data notes that with a figure of $51,314, median household income is still in recovery, increasing by only $1,157 from $50,157 in 2012. Continue reading
Playing on the beach with grandchildren, fishing in mountain streams, and perfecting golf scores…those are fading dreams of retirement for scores of older people in the US. Many have changed or postponed their retirement plans due to job losses, reduced home values, and decimated 401k assets. Some now believe they’ll never retire. Even more alarming is the lack of savings among those of retirement age. According to a survey conducted by the Employee Benefit Research Institute (EBRI), most workers questioned say they have virtually no savings or investments. And 37% of those surveyed think they will have to wait until after age 65 to retire.
When they can least afford it, many seniors are also carrying mortgages and credit card debt. Others have made loans to adult children that have not yet been repaid. AARP comments that 34% of older Americans have used credit cards for basic expenses such as mortgage payments, healthcare, groceries, and utilities. As a result, their average household credit card debt stands at approximately $8,248.
Change has been the constant for the US demographic landscape recently. Two major demographic differences since Census 2000 are the growth of minority populations and changes to household composition. Traditional households of “dad, mom, two kids, and a dog” are no longer the norm. Household types are changing and evolving, so it may be a slow goodbye to the household type portrayed in “Everybody Loves Raymond”, and hello to a group of entirely different kind of households. Continue reading
In 2012, the US population was 313 million. Growing diversity continues to produce striking changes in the population. To provide an accurate way to track these changes, Esri created a proprietary Diversity Index that measures diversity on a scale from 0 to 100. The Diversity Index is defined as the likelihood that two persons, selected at random from the same area, would belong to a different race or ethnic group. For example, if an area’s entire population belongs to the same race or ethnic group, the Index is zero and the area has no diversity. Conversely, if the population can be evenly divided among two or more race or ethnic groups, the area’s Diversity Index increases to 100. The Diversity Index measures only the degree of diversity in an area, not its racial composition. Esri’s Diversity Index for the US has risen from 60.6 in 2010 to 61.4 in 2012, with a forecast to increase to 63.8 within five years. Continue reading
Like it or not, we are all aging. In 2000, the median age in the United States was 35.3 years. By 2010, this number had increased to 37.0 years; today, the median age is 37.3 years. By 2030, seniors will comprise 20 percent of the total US population. In addition to people living longer, the jump in the US median age is also due to aging Baby Boomers.
Seniors are not one monolithic demographic cohort. From those aged 55 to those in their 80s and older, seniors have vastly different lifestyles, preferences, and spending habits. These differences become even more apparent when classified by demographics such as affluence, education, employment, and race/ethnicity. Data about product and media preferences, leisure activities, and shopping habits provides even more detail. Continue reading